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Coefficient of Variation
The standard deviation discussed above is an absolute measure of dispersion. The corresponding relative measure is known as the coefficient of variation. This relative measure of dispersion based upon standard deviation is also called coefficient of standard deviation.
It is used in such problems where we want to compare the variability, homogeneity, stability, uniformity and consistency of two or more series. That series for which the coefficient of variation is greater is said to be more variable or conversely less consistent, less uniform, less stable or less homogeneous. On the other hand, the series for which the Coefficient of Variation is less, is said to be less variable or more consistent, more uniform, more stable or more homogeneous.
Regression Lines It has already been discussed that there are two regression lines and they show mutual relationship between two variable . The regression line Yon X gives th
Standard Deviation The main drawback of the deviation measures of dispersion, as discussed earlier, is that the positive and negative deviations cancel out each other. Use of t
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Assumptions in ANOVA The various populations from which the samples are drawn should be normal and have the same variance. The requirement of normality can be discarded if t
#questionMaximize Z= 3x1 + 2X2 Subject to the constraints: X1+ X2 = 4 X1 - X2 = 2 X1, X2 = 0..
Question: (a) (i) Define the term multicollinearity. (ii) Explain why it is important to guard against multicollinearity. (b) (i) Sometimes we encounter missing values
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I have 5 observations that i must plug into spss. I need an example of 1. I do not know if you are familiar with SPSS but I am going to ask anyway. Subject 1 is a Hispanic male who
how to find mse from ssr table not the anova table
Risk of Portfolios So far, we have seen the application of standard deviation in the context of risk in single investment. But usually most investors hold portfolios of securi
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